The Influence of Medical Expertise and Information Search Skills on Medical Information Searching: Comparative Analysis From a Free Data Set
Notice bibliographique
Résumé
BACKGROUND: Nowadays, the internet has become the primary source of information for physicians seeking answers to medical questions about their patients before consulting colleagues. However, many websites provide low-quality, unreliable information that lacks scientific validation. Therefore, physicians must develop strong information search skills to locate relevant, accurate, and evidence-based content. However, previous studies have shown that physicians often have poor search skills and struggle to find information on the web, which may have detrimental consequences for patient care. OBJECTIVE: This study aims to determine how medical students and residents searched for medical information on the internet, the quality of the web resources they used (including their nature and credibility), and how they evaluated the reliability of these resources and the answers they provided. Given the importance of domain knowledge (in this case, medicine) and information search skills in the search process, we compared the search behaviors of medical students and residents with those of computer science students. While medical students and residents possess greater medical-related knowledge, computer science students have stronger information search skills. METHODS: A total of 20 students participated in this study: 10 medical students and residents, and 10 computer science students. Data were extracted from a freely accessible data set in accordance with FAIR (Findable, Accessible, Interoperable, and Reusable) principles. All participants searched for medical information online to make a diagnosis, select a treatment, and enhance their knowledge of a medical condition-3 primary activities they commonly perform. We analyzed search performance metrics, including search time, the use of medical-related keywords, and the accuracy of the information found, as well as the nature and credibility of web resources used by medical students and residents compared with computer science students. RESULTS: Medical students and residents provided more accurate answers than computer science students without requiring additional time. Their medical expertise also enabled them to better assess the reliability of resources and select high-quality web sources, primarily from hospital websites. However, it is noteworthy that they made limited use of evidence-based tools such as PubMed. CONCLUSIONS: Although medical students and residents generally outperformed computer science students, they did not frequently use evidence-based tools. As previously observed, they may avoid databases due to the risk of encountering too many irrelevant articles and difficulties in applying appropriate filters to locate relevant information. Nevertheless, clinical and practical evidence-based medicine plays a crucial role in updating physicians' knowledge, improving patient care, and enhancing physician-patient relationships. Therefore, information search skills should be an integral part of medical education and continuing professional development for physicians.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».